AI Adoption & Enablement Manager

Synovus•Columbus, GA

About The Position

The AI Adoption and Enablement Manager responsible for accelerating responsible AI usage across the organization—owning intake, prioritization, stakeholder alignment, and enablement programs that translate business needs into scalable AI solutions with measurable impact. The information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job. Synovus is an equal opportunity employer committed to fostering an inclusive work environment.

Requirements

Bachelor's Degree in Computer Science, Information Systems, Business Administration, or related field or an equivalent combination of education and experience.
Eight years of experience as a portfolio manager, preferably in a technology division in a large financial institution.
Knowledge of financial industry regulations and standards
Understanding of technology and project management principles
Strong understanding of technology trends and applications within the financial sector
Strong leadership and decision-making skills
Strong skills in strategic planning, risk management, and financial management
Ability to work with diverse teams and stakeholders at all levels of the organization
Verbal and written communication skills

Responsibilities

Own AI intake and demand shaping: Serve as the front door for AI opportunities—capturing requests, clarifying goals, assessing feasibility, and routing work to the right teams (Data/ML, Product, IT, Legal/Risk, Ops).
Drive adoption with enablement programs: Build and run training, office hours, playbooks, and internal communications that help teams confidently use approved AI tools and workflows.
Translate business needs into AI-ready requirements: Partner with stakeholders to define use cases, success metrics, data needs, constraints, and change impacts—turning ideas into clear problem statements and briefs.
Manage the AI use-case portfolio: Maintain a prioritized backlog, facilitate scoring (value, effort, risk), and provide visibility into pipeline health, milestones, and outcomes.
Champion responsible AI: Embed governance into the process by coordinating reviews for privacy, security, compliance, and model risk; ensure tools and solutions meet internal standards.
Measure impact and tell the story: Track adoption, productivity gains, quality improvements, and ROI; publish dashboards, case studies, and success highlights to sustain momentum.
Create a repeatable operating model: Establish lightweight processes, templates, and tooling for intake, evaluation, experimentation, rollout, and ongoing support.
Partner across functions to scale: Act as a connector between business teams and technical delivery—aligning priorities, removing blockers, and ensuring solutions land well in day-to-day work.
Each team member is expected to be aware of risk within their functional area. This includes observing all policies, procedures, laws, regulations and risk limits specific to their role. Additionally, they should raise and report known or suspected violations to the appropriate Company authority in a timely fashion.
Performs other related duties as required.